ClaudeScientist

A research co-pilot that remembers, verifies, and lets you steer.

中文版本: README.zh-CN.md

ClaudeScientist plugs into Claude Code or Codex and adds what most AI scientist systems leave out: it remembers what you've tried, verifies your numbers before you publish them, and gives you a live terminal dashboard where you can watch the research unfold and step in at any time.

You give the agent a research question. It generates hypotheses, ranks them in a tournament, runs experiments with built-in safety checks, and tracks provenance for every number it produces. You watch the whole process in a second terminal and can reject, redirect, or approve at any point.

Current version: v5.0.0 — the cockpit is now an "activity streaming" research monitor. The top of the screen shows a phase strip (idle / explore / select / experiment / verify / prove / review / narrate) derived live from cockpit_events; the main pane shows activity cards (one card per research action — a BT tournament, a proof diagnose loop, a Lean attempt) instead of a flat event firehose; a new Focus tab lists the node(s) the agent is working on right now. The original event stream is preserved as a collapsible audit log at the bottom (toggle with A). Two new optional MCP atomic tools — cockpit__set_phase and cockpit__narrate — let SOP-driven agents annotate decisions without coupling to the cockpit's rendering. No schema migration: phase / focus / activity are pure functions over the existing cockpit_events table, per ADR 0011 and architecture.md §14.

v4.2.0 features retained (see retrospective-v4.2.md): tab grouping into Cross / Empirical / Proof, collapsible detail sections, pane-scoped w/i/t keys, the multi-provider vector backend (DashScope / Jina / Voyage / GLM tested via ADR 0010, default local Qwen/Qwen3-Embedding-0.6B), reports-as-files (closure / draft / diagnostic / portfolio / cascade) per ADR 0009, and the cold-start Welcome screen. See architecture.md §13 for the two-trunk split.

What it looks like

Open two terminals side by side. That's the whole UI.

<picture> <img alt="Cockpit TUI screenshot" src="docs/assets/image2.png" width="800"> </picture>

The cockpit TUI — hypothesis tree, evidence, ratings, and event stream in one terminal.

The two terminals don't talk to each other directly — they both read and write the same SQLite file. This is the central design choice: every module collaborates through a shared database, not over the network.

What you can do with it

• Track your research thinking. Every hypothesis, piece of evidence, and branching decision lives in a persistent graph. Papers you read along the way are compressed and searchable. Come back next week — it's all there. Want to revisit a direction you pruned? Run a counterfactual replay without touching the live state.
• Rank competing ideas. A Bradley-Terry tournament compares hypotheses head-to-head and produces a leaderboard with confidence intervals, so you know which direction is actually winning.
• Lock your goalposts before experimenting. Preregistration makes you commit to a metric, direction, and threshold before you see results. Multiple-comparison correction is applied automatically.
• Make your numbers trustworthy. Every reported number gets checked: Is it reproducible across random seeds? Which files produced it? Has anything changed since? Baseline comparisons are checked for fair compute budgets. A reviewer agent blocks any unverified claim from reaching a writeup.
• Catch mistakes before they compound. A failure ledger remembers every debugging session. Next time you hit a similar problem, the system surfaces how you fixed it before.
• Watch and steer in real time. The cockpit TUI shows the hypothesis tree, ratings, and event stream live. Press a key to reject a bad hypothesis or inject a note — interventions are picked up at the next turn.
• Generate and verify statistical proofs (v4.0). A proof trunk handles drafting, segmentation, diagnosis against known error patterns, and optional Lean 4 formal verification.

Quick start

Install and run the setup wizard:

uv sync
uv run python -m claudescientist.setup

The wizard walks you through agent-host selection (claude, codex, or both), embedding backend, proof corpus seeding, held-out directory, Lean toolchain, and auto-prune — all in one pass. Run it again any time; it skips steps that are already done.

For non-interactive setup, set CLAUDESCIENTIST_SETUP_AGENT_HOST=codex or CLAUDESCIENTIST_SETUP_AGENT_HOST=both. Codex support is project-local: setup generates .codex/config.toml, .codex/agents/*.toml, and repo skills under .agents/skills/ from the existing Claude Code assets.

Literature search uses two external MCPs. arXiv is launched through uv tool run arxiv-mcp-server; OpenAlex is launched through npx -y openalex-research-mcp, so install Node.js/npm if you want the OpenAlex-backed librarian tools.

<details><summary>Manual setup (without the wizard)</summary>

uv sync --extra proof    # pulls in sentence-transformers for the proof trunk
uv run python scripts/seed_proof_corpus.py
uv run python scripts/seed_proof_failures.py

</details>

Run — open two terminals from the repo root:

# Terminal A: Claude Code (from the repo root)
claude

# Or Terminal A: Codex (after choosing codex/both in setup)
codex

# Terminal B: cockpit TUI (from the repo root)
uv run python -m cockpit.tui

For the Chinese UI on Windows Terminal:

chcp 65001
$env:PYTHONUTF8=1
uv run python -m cockpit.tui --lang zh

Press L inside the TUI to toggle English / Chinese labels.

Lean formal verification is a separate opt-in setup — see docs/setup-lean.md.

Where to go next

If you're new, read in this order:

1. [`docs/overview.md`](docs/overview.md) — the complete mental model: how the pieces fit, what happens end-to-end, the three design principles
2. [`docs/workflows/first-research-task.md`](docs/workflows/first-research-task.md) — walk through one full task from start to finish
3. [`docs/architecture.md`](docs/architecture.md) — the contracts between modules (treat as binding)
4. [`docs/tool-reference.md`](docs/tool-reference.md) — every MCP tool, with signature and usage guidance

More:

• Design rationale for each major decision → docs/adr/
• Where the project is headed → docs/roadmap.md
• Historical plans → docs/archive/
• Agent and contributor rules → AGENTS.md

Runtime details

Default paths:

• Shared state: .research-agent/state.db under the repo root
• Generated reports: reports/ under the repo root; gitignored by default,

force-add individual files only when you intentionally want to share them

• Held-out datasets: %USERPROFILE%\.research-agent\heldout, configurable via RESEARCH_AGENT_HELDOUT_DIR
• Embedding backend: local (sentence-transformers/Qwen/Qwen3-Embedding-0.6B); override with RESEARCH_AGENT_EMBED_BACKEND=mock|openai. Tests use mock automatically.

Dev server commands for individual MCP modules:

uv run python -m memory_mcp.dev_server
uv run python -m verify_mcp.dev_server
uv run python -m prove_mcp.dev_server
uv run python -m cockpit.mcp_server
uv run python -m claudescientist.heldout register <name> <path>

Validation

Before shipping a change:

uv run ruff check
uv run pytest tests/memory_mcp tests/verify_mcp tests/prove_mcp tests/hooks tests/cockpit tests/scripts tests/e2e
uv run python -m cockpit.tui --once --lang zh
uv run python -c "import memory_mcp.server; import verify_mcp.server; import prove_mcp.server; import cockpit.mcp_server; print('OK')"

Current status

The repo works for local development and integration. A fresh end-to-end validation pass is needed before calling it production-ready.

A few things to know:

• Auto-prune is dry-run by default. Set RESEARCH_AGENT_AUTO_PRUNE=1 to let it actually pause weak branches.
• The cockpit is terminal-only. No browser frontend, no web server.
• The prover agent works without Lean. The NL proof workflow runs on its own; Lean is extra insurance you can set up later via docs/setup-lean.md.
• `mem_nodes.elo_score` is a legacy column. New code should read mem_bt_ratings.strength.

Full tool list and scope details: docs/tool-reference.md and AGENTS.md.